The ovary. Computed tomography and magnetic resonance imaging.
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CT and MR imaging offer valuable insights into benign and malignant ovarian masses, with MR imaging's superior soft tissue contrast and multiplanar capabilities proving particularly useful for evaluating various ovarian conditions and disorders of sexual differentiation.
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Abstract
CT and MR imaging can both contribute valuable clinical information in women with benign and malignant ovarian masses; the superior soft tissue contrast and multiplanar capabilities provided by MR imaging make it a valuable tool to evaluate the normal ovary, polycystic ovaries, endometriosis, and disorders of sexual differentiation. CT is currently the recommended modality to stage ovarian carcinoma, and peritoneal implants as small as 5 mm can be visualized. With the addition of contrast-enhanced images to conventional MR sequences, however, improved visualization of intratumoral architecture has also allowed for accurate MR characterization of benign versus malignant ovarian masses. Fat saturation techniques used with conventional MR sequences can also be used for definitive characterization of benign fat-containing teratomas and differentiate these tumors from hemorrhagic ovarian cysts or endometriomas. Finally, the detailed visualization of the normal-sized ovary on MR images provided by both the body coil and the new phased-array coil allows detection of the normal ovaries, ovarian follicles, and ovarian cysts throughout the premenopausal and postmenopausal years. Findings of polycystic ovarian syndrome, which cannot be evaluated by CT, are characteristic on MR images. MR is unparalleled in the evaluation of disorders of sexual differentiation because MR images can depict ectopic and normally positioned gonads and provide multiplanar depiction of the other pelvic organs and perineum as well. CT and MR imaging can provide valuable and specific clinical information about the ovary and benign and malignant ovarian disease.
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- europepmc
- last seen: 2026-06-11T06:19:48.454388+00:00
- openalex
- last seen: 2026-06-04T00:00:01.174412+00:00
- pubmed
- last seen: 2026-05-13T22:11:34.315996+00:00
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